Broadcast color video signals conventionally comprise three component signals: a luminance signal, designated as Y, which carries the image contrast--black and white--information, and two chrominance signals, designated either as I and Q or (R-Y) and (B-Y), which carry the image color information. Composite video, such as the NTSC video signal that is the standard for color television transmissions in North America, combines the three analog component signals for transmission by modulating a carrier with both of the chrominance signals in phase-quadrature and then interleaving the combined chrominance signal with the baseband luminance signal. Component video, however, treats the analog baseband luminance and chrominance signals as separate channels and does not combine them in analog form. Component video produces a higher-quality image than composite video because it avoids crosstalk between the three analog components that would be introduced by combining them as in composite video, and because it can allow for more bandwidth for the chrominance components of the signal than does the NTSC composite video format.
Digital signal transmissions are less susceptible than analog signal transmissions to noise and other image degradations introduced during transmission; hence, the quality of a received video image can be enhanced further by means of digital video signal distribution. The frequency, or bit rate, required for digital transmission of component video is determined by the sampling rate and bits per sample for each of the luminance and chrominance signals. The sampling rate and the number of bits used per sample are generally directly related to the image resolution and quality. Image quality is thus generally directly related to the transmission bit rate, and hence it is desirable to keep the transmission rate at a maximum. However, conventional transmission facilities are generally limited in the transmission rate that they can handle, and the cost of a transmission facility is generally directly related to the maximum rate that it can handle. Hence it is desirable to keep the transmission rate to a minimum.
These conflicting considerations have resulted in numerous techniques and arrangements that have imaginatively sought to reduce the transmission rate of component video signals. An example of such an analog technique is to greatly limit the bandwidth of chrominance signals--to 0.5 MHz, for example--and even of the luminance signals, to reduce the frequency at which the signals need be sampled during digitization. This technique, however, leads to excessive distortion of, and lack of resolution in, the video image. Information on image detail is carried at the higher frequencies. Hence, the lower is the signal bandwidth, the more of the detail is lost from the image.
Another example of an analog technique takes advantage of the periodicity of the video signals' spectrum to reduce the sampling rate, by sampling the video signals at sub-Nyquist frequencies. The Nyquist frequency is twice the maximum frequency contained by the signal and theoretically is the lowest frequency at which a given signal may be sampled such that the samples retain all information content of the sampled signal. The disadvantage of this approach is that sub-Nyquist sampling results in image distortion, due to aliasing, and hence degrades the image quality.
Aside from their idiosyncratic failings, analog rate reduction techniques share certain disadvantages that digital rate reduction techniques do not have. Their major disadvantage is the degradation that they produce in the signal-to-noise ratio, which degradation results in presence of noise and errors in the reproduced image. Another disadvantage common to analog rate reduction techniques is the difficulty of manipulating analog video signals. For example, sharp analog signal filters are both difficult to implement and cause distortions in the video signals. Hence the art has tended to turn to digital techniques when it has sought to reduce video transmission rate without sacrificing greatly video image quality.
Various techniques for image compression are available in the digital domain, that is, once the image has been digitized. One such technique is interleaved subsampling, which discards every sample of one phase (i.e., every other sample) of an image scan line and every sample of the opposite phase of an adjacent scan line, and instead of each discarded sample merely transmits an interpolation code indicating whether values of horizontally adjacent samples (adjacent samples on the same scan line), of vertically adjacent samples (adjacent samples on adjacent scan lines), or of diagonally adjacent samples are to be used at the receiver to interpolate the value of the discarded sample. Another technique, related to interleaved subsampling, takes advantage of the fact that the value of chrominance signals tends to vary directly as the value of luminance signals, and hence transmits merely the luminance interpolation code and uses this code to interpolate both the luminance and the chrominance discarded sample values.
Yet another compression technique is differential pulse code modulation (DPCM), which reduces the number of bits required to transmit the value of a sample by only transmitting information about the difference of a sample from its predicted value. The predicted value is derived from the values of preceding samples. The art has sought to reduce image degradation that results from DPCM by use of adaptive quantization, a technique that uses a plurality of "scales"--quantizers--for measuring differences between samples and their predicted values, and for each sample selects and uses the "scale" thought best for minimizing granularity of information that is most significant to duplicating the appearance of the original sample in the reconstructed sample. Selection of the "scale" is based on a value calculated from predicted values of a plurality of preceding samples. Implementations of this technique have been only marginally successful in achieving their objective, primarily because the values of preceding samples are not necessarily good predictors of the optimum "scale" applicable to a current sample.
Their generally superior performance over analog techniques notwithstanding, the digital compression techniques eliminate or only approximate certain image information, and to that extent they result in image degradation. Therefore, in order to keep image quality high, it has heretofore not been possible to fully exploit the rate reduction capabilities possessed by combinations of these techniques. Hence, the transmission rate for high-quality images has remained undesirably high. What the art requires is further reduction in high-quality image transmission rates without substantial deterioration of the image quality in the process.